We show a violin plot that displays the distribution of correlation values for each active metric filter, whereas multiple models or datasets are shown next to each other ( fig:application B).
Here, brushing can be used to adjust the filter, which manifests in the annotations that are displayed in fig:application C.
The same behavior can be achieved by modifying the filter limits of fig:application A, which allow for a more exact filter specification.
With this visualization approach, we follow the Guidelines for using multiple views in information visualization and implement brushing and linking [1]}.
Filters can also be combined, as shown in fig:embeddings A, such that even more fine-grained data subsets can be inspected.
